In this episode, we discuss the bane of many machine learning algorithms – overfitting. It is also explained why it is an undesirable way to learn and how to combat it via L1 and L2 regularization.
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The paper “Regression Shrinkage and Selection via the Lasso” is available here:
Andrej Karpathy’s excellent lecture notes on neural networks and regularization:
The neural network demo is available here:
A playlist with out neural network and deep learning-related videos:
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